Face recognition method based on joint sparse discriminant analysis and system thereof

A technology of face recognition and discriminant analysis, which is applied in character and pattern recognition, instruments, computing, etc., and can solve problems such as unsatisfactory recognition rate of face recognition systems

Active Publication Date: 2017-09-01
SHENZHEN UNIV
View PDF2 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a face recognition method based on joint sparse discriminant analysis, aiming to solve the problem of the recognition rate of the face recognition system under the situation that there are many changes in the face in terms of illumination, angle, expression, camouflage and posture. suboptimal technical issues

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Face recognition method based on joint sparse discriminant analysis and system thereof
  • Face recognition method based on joint sparse discriminant analysis and system thereof
  • Face recognition method based on joint sparse discriminant analysis and system thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] figure 1 The flow chart of the face recognition method based on joint sparse discriminant analysis provided by the present invention is shown, and the weather book is as follows:

[0067] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0068] Suppose the face image matrix X=[x 1 , x 2 ,...,x n ]∈R d×n , where n is the number of training samples, and d is the size of each sample image. By projecting the original high-dimensional data to a low-dimensional projection matrix B∈R d×k (k is the image size after dimensionality reduction, k≤d) to achieve dimensionality reduction and feature extraction. The method comprises the steps of:

[0069] Step S1, establishing a database storing face training images of known identities;

[0070] The establishment of the database of described human face training image comprises the following steps:

[0071] S11, collecting color or black and white pic...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention is applicable to the field of improvement on a computer vision technology, and provides a face recognition method based on joint sparse discriminant analysis. The method comprises steps: A, a database for storing face training images with known identities is built; B, detection on a face with a to-be-detected identity and data acquisition are carried out, and a face database with authentication is built; C, feature extraction is carried out on to-be-authenticated face data and training data, and a discriminant analysis model based on joint sparse representation is built; and D, by using the training data after feature extraction in the step C and the to-be-authenticated data and in combination of corresponding label information, a nearest neighbor classifier is used for discriminant analysis, and a face recognition result is calculated. By adopting the joint sparse discriminant analysis to recognize the to-be-authenticated face image, the authentication accuracy is improved, and the recognition robustness in a condition with multiple changes of the to-be-authenticated face in aspects such as light, angle, expression, disguise and gesture can be effectively improved.

Description

technical field [0001] The invention belongs to the field of computer vision technology improvement, in particular to a face recognition method and system based on joint sparse discriminant analysis. Background technique [0002] In recent years, with the development of social economy, the standard of human life is getting higher and higher. While enjoying the great changes brought about by high-tech products to the traditional way of life, people are constantly exploring a smarter and more humane way of life. Innovative concepts such as "Internet +" and "Smart City" have emerged in the trend of technological development. The country, government, and enterprises have all attached great importance to the construction of artificial intelligence. At present, the development of technology in the field of computer vision has made great contributions to society. Technologies such as fingerprint recognition and face recognition have been widely used in entry-exit identity verific...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/172G06F18/2136G06F18/2135G06F18/24147
Inventor 赖志辉莫冬梅
Owner SHENZHEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap